wooders
Joined 10 years ago
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Comment · 4 months ago
Comment · 10 months ago
I think the problem with ChatGPT / other RAG-based memory solutions is that it's not possible to collaborate with the agent on what it's memory should look like - so it makes sense that its much easier to just have a stateless system and message queue, to avoid mysterious pollution. But Letta's memory management is primarily text/files based so very transparent and controllable.
An example of how this kind of memory can help is learned skills https://www.letta.com/blog/skill-learning - if your agent takes the time to reflect/learn from experience and create a skill, that skills is much more effective at making it better next time than just putting the raw trajectory into context.
Comment · 1 year ago
FYI the LOCOMO benchmarking done by Mem0 was very sus so I wouldn't recommend relying on those numbers for anything
https://www.reddit.com/r/LocalLLaMA/comments/1mon8it/woah_le...
https://www.reddit.com/r/LangChain/comments/1kg5qas/lies_dam...
Comment · 1 year ago
I think the "memory blocks" are essentially what you are describing - to have an infinite session (which systems like Letta is designed for) you have to have a mechanism for organizing the important information and persisting it for future interactions. This organization can be done via tool calls (which was what MemGPT did) or done by other agents in the background. While the message buffer is continues to grow / old messages get evicted, the memory blocks are fixed size and always in context.
Comment · 1 year ago
Agents are already usually deployed as an API service. You can have "agent-to-agent" communication by having agents call each others APIs. I don't understand what this protocol is for.
MCP actually fills a gap since people don't normally expose things like writing to their local filesystem as a callable API.
(disclaimer: I work on Letta Code)